{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:P2UWJTDMOURVZQKN74LYBQHM45","short_pith_number":"pith:P2UWJTDM","canonical_record":{"source":{"id":"1706.00672","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-05-31T18:03:33Z","cross_cats_sorted":[],"title_canon_sha256":"1b0068d4c476cb2ff334774d6ed41f69b7c45d5b1fe5c009b92f7bd58aa792ba","abstract_canon_sha256":"8ce4b97bb1cf74a46a33399dc8c6661edf8cf3c4f5f2814f73e1bf60b1197cd2"},"schema_version":"1.0"},"canonical_sha256":"7ea964cc6c75235cc14dff1780c0ece75f8d514ec2c2a97d3a61f04c954e5725","source":{"kind":"arxiv","id":"1706.00672","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1706.00672","created_at":"2026-05-17T23:54:56Z"},{"alias_kind":"arxiv_version","alias_value":"1706.00672v5","created_at":"2026-05-17T23:54:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1706.00672","created_at":"2026-05-17T23:54:56Z"},{"alias_kind":"pith_short_12","alias_value":"P2UWJTDMOURV","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_16","alias_value":"P2UWJTDMOURVZQKN","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_8","alias_value":"P2UWJTDM","created_at":"2026-05-18T12:31:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:P2UWJTDMOURVZQKN74LYBQHM45","target":"record","payload":{"canonical_record":{"source":{"id":"1706.00672","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-05-31T18:03:33Z","cross_cats_sorted":[],"title_canon_sha256":"1b0068d4c476cb2ff334774d6ed41f69b7c45d5b1fe5c009b92f7bd58aa792ba","abstract_canon_sha256":"8ce4b97bb1cf74a46a33399dc8c6661edf8cf3c4f5f2814f73e1bf60b1197cd2"},"schema_version":"1.0"},"canonical_sha256":"7ea964cc6c75235cc14dff1780c0ece75f8d514ec2c2a97d3a61f04c954e5725","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:54:56.846544Z","signature_b64":"PRXDJ7vgow2Se8irn/YWNVZZtPaqS5gCAO7DlVq2v5R44gCQfaq951rCi1siSXHaBR2wW1spu0z4cshtxJzhCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7ea964cc6c75235cc14dff1780c0ece75f8d514ec2c2a97d3a61f04c954e5725","last_reissued_at":"2026-05-17T23:54:56.846054Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:54:56.846054Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1706.00672","source_version":5,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:54:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DLxh3XaONYs2ug51mNx156ON01VAe9iJthNrvy5JoO4fE7E2vrYOsWet4WzuSS70SZscWODveFQDRZ2q+DgtAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T06:10:35.084387Z"},"content_sha256":"3010bf84e43c0267078fb7720b29b8373b93fb33088cd82b892204ffa78a730b","schema_version":"1.0","event_id":"sha256:3010bf84e43c0267078fb7720b29b8373b93fb33088cd82b892204ffa78a730b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:P2UWJTDMOURVZQKN74LYBQHM45","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Development of a N-type GM-PHD Filter for Multiple Target, Multiple Type Visual Tracking","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Andrew Wallace, Nathanael L. Baisa","submitted_at":"2017-05-31T18:03:33Z","abstract_excerpt":"We propose a new framework that extends the standard Probability Hypothesis Density (PHD) filter for multiple targets having $N\\geq2$ different types based on Random Finite Set theory, taking into account not only background clutter, but also confusions among detections of different target types, which are in general different in character from background clutter. Under Gaussianity and linearity assumptions, our framework extends the existing Gaussian mixture (GM) implementation of the standard PHD filter to create a N-type GM-PHD filter. The methodology is applied to real video sequences by i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1706.00672","kind":"arxiv","version":5},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:54:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VnwJXlgyu/Onr2qSGolSYHp/s0/PBlhtYAbaQ+tIFBnYfoSoJUkOkqBUuYQ60BBPgKqOOefE2X+fYMG6++8bCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T06:10:35.084935Z"},"content_sha256":"939a090a000a84ea5e058f3bb0d6d73fcaa34b44e5416366f82b3525bef7aa52","schema_version":"1.0","event_id":"sha256:939a090a000a84ea5e058f3bb0d6d73fcaa34b44e5416366f82b3525bef7aa52"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/P2UWJTDMOURVZQKN74LYBQHM45/bundle.json","state_url":"https://pith.science/pith/P2UWJTDMOURVZQKN74LYBQHM45/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/P2UWJTDMOURVZQKN74LYBQHM45/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-04T06:10:35Z","links":{"resolver":"https://pith.science/pith/P2UWJTDMOURVZQKN74LYBQHM45","bundle":"https://pith.science/pith/P2UWJTDMOURVZQKN74LYBQHM45/bundle.json","state":"https://pith.science/pith/P2UWJTDMOURVZQKN74LYBQHM45/state.json","well_known_bundle":"https://pith.science/.well-known/pith/P2UWJTDMOURVZQKN74LYBQHM45/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:P2UWJTDMOURVZQKN74LYBQHM45","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"8ce4b97bb1cf74a46a33399dc8c6661edf8cf3c4f5f2814f73e1bf60b1197cd2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-05-31T18:03:33Z","title_canon_sha256":"1b0068d4c476cb2ff334774d6ed41f69b7c45d5b1fe5c009b92f7bd58aa792ba"},"schema_version":"1.0","source":{"id":"1706.00672","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1706.00672","created_at":"2026-05-17T23:54:56Z"},{"alias_kind":"arxiv_version","alias_value":"1706.00672v5","created_at":"2026-05-17T23:54:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1706.00672","created_at":"2026-05-17T23:54:56Z"},{"alias_kind":"pith_short_12","alias_value":"P2UWJTDMOURV","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_16","alias_value":"P2UWJTDMOURVZQKN","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_8","alias_value":"P2UWJTDM","created_at":"2026-05-18T12:31:37Z"}],"graph_snapshots":[{"event_id":"sha256:939a090a000a84ea5e058f3bb0d6d73fcaa34b44e5416366f82b3525bef7aa52","target":"graph","created_at":"2026-05-17T23:54:56Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"We propose a new framework that extends the standard Probability Hypothesis Density (PHD) filter for multiple targets having $N\\geq2$ different types based on Random Finite Set theory, taking into account not only background clutter, but also confusions among detections of different target types, which are in general different in character from background clutter. Under Gaussianity and linearity assumptions, our framework extends the existing Gaussian mixture (GM) implementation of the standard PHD filter to create a N-type GM-PHD filter. The methodology is applied to real video sequences by i","authors_text":"Andrew Wallace, Nathanael L. Baisa","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-05-31T18:03:33Z","title":"Development of a N-type GM-PHD Filter for Multiple Target, Multiple Type Visual Tracking"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1706.00672","kind":"arxiv","version":5},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:3010bf84e43c0267078fb7720b29b8373b93fb33088cd82b892204ffa78a730b","target":"record","created_at":"2026-05-17T23:54:56Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"8ce4b97bb1cf74a46a33399dc8c6661edf8cf3c4f5f2814f73e1bf60b1197cd2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-05-31T18:03:33Z","title_canon_sha256":"1b0068d4c476cb2ff334774d6ed41f69b7c45d5b1fe5c009b92f7bd58aa792ba"},"schema_version":"1.0","source":{"id":"1706.00672","kind":"arxiv","version":5}},"canonical_sha256":"7ea964cc6c75235cc14dff1780c0ece75f8d514ec2c2a97d3a61f04c954e5725","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7ea964cc6c75235cc14dff1780c0ece75f8d514ec2c2a97d3a61f04c954e5725","first_computed_at":"2026-05-17T23:54:56.846054Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:54:56.846054Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PRXDJ7vgow2Se8irn/YWNVZZtPaqS5gCAO7DlVq2v5R44gCQfaq951rCi1siSXHaBR2wW1spu0z4cshtxJzhCA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:54:56.846544Z","signed_message":"canonical_sha256_bytes"},"source_id":"1706.00672","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3010bf84e43c0267078fb7720b29b8373b93fb33088cd82b892204ffa78a730b","sha256:939a090a000a84ea5e058f3bb0d6d73fcaa34b44e5416366f82b3525bef7aa52"],"state_sha256":"76d3780d0ce11b187b89a254569faf9eeb9c562751b54e16506c30baad1903f0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"drV86i1Nvp6qeByDKGgHnREWqvZC9IHV7bDhZ2+Tmh1EON6pxPeDFuT7Wfq+XEtsgxmuz1sIHh9t5G3jIsxlDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-04T06:10:35.087900Z","bundle_sha256":"69c37b8becfa2155d3d3af076ee067ccc0574f01ca4bef7dcd14e59824e7f0db"}}